Bibliographic record
Abstract
Background: The development of eating disorders (EDs) and disordered eating pathology (DEP) is related to a complex interplay of various factors, with the media being a main risk factor. The high comorbidity related to EDs and DEP highlights the importance of preventive interventions and requires additional prevention strategies that create opportunities for policy changes, while targeting media influences. In 2012, Israel initiated the “models’ law”, setting limits on both the employment of underweight models and the use of photo editing. This study examined the impact of the models’ law on body dissatisfaction, DEP, and EDs among young women in Israel. Methods: The study included two parts: self-report questionnaires and a telephone interview. The sample of 203 women was divided into two age groups, 81 women aged 18-24 and 122 women aged 25-35-that completed both parts of the study. Results: The models’ law had significantly higher impact on younger as opposed to older participants. Yet younger participants were found to have higher levels of DEP than the older participants. Additionally, participants who were highly supportive of the law had lower levels of DEP. Conclusion: The results indicate that younger participants had higher levels of DEP and were more influenced by the thin ideal and the media. Thus, these results highlight the importance of implementing prevention programs at younger ages and expanding the spectrum of prevention programs to the field of policy change, using legislation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".